import eia_api as api
import eia_data
import pandas as pd
import numpy as np
import requests
import json
import os
import datetime
import plotly.express as px
import great_tables as gtEIA API - Data Refrsh (Python Version)
Load libraries
API Settings:
raw_json = open("../metadata/series.json")
meta_json = json.load(raw_json)
series = pd.DataFrame(meta_json["series"])
api_path = meta_json["api_path"]
facets_template = {
"parent" : None,
"subba" : None
}
offset = 2250
eia_api_key = os.getenv('EIA_API_KEY')
meta_path = "../metadata/ciso_log_py.csv"
data_path = "../csv/ciso_grid_py.csv"# api_metadata = api.eia_metadata(api_key = eia_api_key, api_path = api_path)
# print(api_metadata.meta["endPeriod"])
# end = pd.to_datetime(api_metadata.meta["endPeriod"])
# print(end)meta_obj = eia_data.get_metadata(api_key = eia_api_key, api_path = api_path, meta_path = meta_path, series = series)
gt.GT(meta_obj.request_meta,)| parent | subba | end_act | request_start | end | updates_available |
| CISO | PGAE | 2024-08-26 07:00:00 | 2024-08-26 08:00:00 | 2025-01-27 07:00:00 | True |
| CISO | SCE | 2024-08-23 07:00:00 | 2024-08-23 08:00:00 | 2025-01-27 07:00:00 | True |
| CISO | SDGE | 2024-11-01 07:00:00 | 2024-11-01 08:00:00 | 2025-01-27 07:00:00 | True |
| CISO | VEA | 2024-11-01 07:00:00 | 2024-11-01 08:00:00 | 2025-01-27 07:00:00 | True |
m = meta_obj.request_meta
index = meta_obj.last_index + 1
data = None
for i in m.index:
facets = facets_template
facets["parent"] = m.at[i, "parent"]
facets["subba"] = m.at[i, "subba"]
start = m.at[i, "request_start"]
end = m.at[i, "end"]
print(facets)
if m.at[i, "updates_available"]:
temp = api.eia_backfill(api_key = eia_api_key,
api_path = api_path+ "data",
facets = facets,
start = start.to_pydatetime()- datetime.timedelta(hours = 24),
end = end.to_pydatetime() + datetime.timedelta(hours = 24),
offset = offset)
temp.data = temp.data[(temp.data["period"] <= end.to_pydatetime()) & (temp.data["period"] >= start.to_pydatetime())]
ts_obj = pd.DataFrame(np.arange(start = start, stop = end + datetime.timedelta(hours = 1), step = datetime.timedelta(hours = 1)).astype(datetime.datetime), columns=["index"])
ts_obj = ts_obj.merge(temp.data, left_on = "index", right_on = "period", how="left")
ts_obj.drop("period", axis = 1, inplace= True)
ts_obj = ts_obj.rename(columns= {"index": "period"})
else:
ts_obj = None
print("No new data is available")
meta_temp = eia_data.create_metadata(data = ts_obj, start = start, end = end, type = "refresh")
if ts_obj is None:
meta_temp["parent"] = m.at[i, "parent"]
meta_temp["subba"] = m.at[i, "subba"]
if meta_temp["success"]:
print("Append the new data")
d = eia_data.append_data(data_path = data_path, new_data = ts_obj, save = True)
meta_temp["update"] = True
else:
meta_temp["update"] = False
meta_temp["comments"] = meta_temp["comments"] + "The data refresh failed, please check the log; "
meta_df = pd.DataFrame([meta_temp])
if data is None:
data = ts_obj
else:
data = data._append(ts_obj)
if i == series.index.start:
meta_new = meta_df
else:
meta_new = meta_new._append(meta_df){'parent': 'CISO', 'subba': 'PGAE'}
{'parent': 'CISO', 'subba': 'SCE'}
{'parent': 'CISO', 'subba': 'SDGE'}
{'parent': 'CISO', 'subba': 'VEA'}gt.GT(meta_new,rowname_col = "index")| parent | subba | time | start | end | start_act | end_act | start_match | end_match | n_obs | na | type | update | success | comments | |
| CISO | PGAE | 2025-01-27 12:03:45.718008+00:00 | 2024-08-26 08:00:00 | 2025-01-27 07:00:00 | 2024-08-26 08:00:00 | 2025-01-27 07:00:00 | True | True | 3696 | 77 | refresh | False | False | Missing values were found; The data refresh failed, please check the log; | |
| CISO | SCE | 2025-01-27 12:03:47.359813+00:00 | 2024-08-23 08:00:00 | 2025-01-27 07:00:00 | 2024-08-23 08:00:00 | 2025-01-27 07:00:00 | True | True | 3768 | 86 | refresh | False | False | Missing values were found; The data refresh failed, please check the log; | |
| CISO | SDGE | 2025-01-27 12:03:48.216144+00:00 | 2024-11-01 08:00:00 | 2025-01-27 07:00:00 | 2024-11-01 08:00:00 | 2025-01-27 07:00:00 | True | True | 2088 | 71 | refresh | False | False | Missing values were found; The data refresh failed, please check the log; | |
| CISO | VEA | 2025-01-27 12:03:48.966389+00:00 | 2024-11-01 08:00:00 | 2025-01-27 07:00:00 | 2024-11-01 08:00:00 | 2025-01-27 07:00:00 | True | True | 2088 | 71 | refresh | False | False | Missing values were found; The data refresh failed, please check the log; |
meta_updated = eia_data.append_metadata(meta_path = meta_path, meta = meta_new, save = True, init = False)Plot the Series
We will use Plotly to visualize the series:
if data is not None:
d = data.sort_values(by = ["subba", "period"])
p = px.line(data, x="period", y="value", color="subba")
p.show()
else:
print("No new data is available")full_data = pd.read_csv(data_path)
full_data.head()
full_data["period"] = pd.to_datetime(full_data["period"])
p = px.line(full_data, x="period", y="value", color="subba")
p.show()